Results on the KITTI dataset [1]} are evaluated using average precision \((\mathrm {AP}|_{R_{40}})\) . The evaluation is separated by difficulty settings (Easy, Moderate, and Hard) and by object class (Car, Pedestrian, and Cyclist). The Car class has an IoU criteria of 0.7 while the Pedestrian and Cyclist classes have an IoU criteria of 0.5, where IoU criteria is a threshold to be considered a true positive detection.
